{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/jermwatt/machine_learning_refined/blob/main/notes/13_Multilayer_perceptrons/13_3_Optimization.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6cVOsKckeDmP"
   },
   "source": [
    "## Chapter 13: Multi-layer Perceptrons "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook contains interactive content from an early draft of the university textbook <a href=\"https://github.com/neonwatty/machine-learning-refined/tree/main\">\n",
    "Machine Learning Refined (2nd edition) </a>.\n",
    "\n",
    "The final draft significantly expands on this content and is available for <a href=\"https://github.com/neonwatty/machine-learning-refined/tree/main/chapter_pdfs\"> download as a PDF here</a>."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NGF3icB7eDmQ"
   },
   "source": [
    "# 13.3  Optimization of Neural Network Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Zu6ghG6XeDmQ"
   },
   "source": [
    "Most learning models employing multi-layer perceptron units are often highly non-convex, a fact that for many years made them difficult to optimize properly. However in addition to many recently created ideas (starting in the early 2000s) that help significantly with the problem of tuning these models, for example the concept of *batch normalization*, we saw in Part I of this text that non-convexity is not by itself not necessarily prohibitive to proper parameter tuning. This is especially true with *first order methods*, i.e., methods derived from gradient descent (as detailed in Sections 3.6 - 3.9), which are the most popular optimization tools used to tune models employing multi-layer perceptrons. Indeed while they are universally applicable many of the practical advanced first order methods described there for extending the standard gradient descent algorithm to better deal with non-convexity were first developed by researchers aiming to improve standard optimization methods to better enable learning with multi-layer perceptrons.\n",
    "\n",
    "In this Section broadly review the issue of non-convexity when employing multi-layer perceptrons, and highlight those tools introduced in Part I of the text that are especially relevant at optimizing such models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "zAi8T1KUeDmR"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: github-clone in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (1.2.0)\n",
      "Requirement already satisfied: requests>=2.20.0 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from github-clone) (2.32.3)\n",
      "Requirement already satisfied: docopt>=0.6.2 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from github-clone) (0.6.2)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (3.4.0)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (3.10)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (2.2.3)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (2024.12.14)\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.3.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "chapter_13_datasets already cloned!\n",
      "chapter_13_library already cloned!\n",
      "chapter_13_images already cloned!\n",
      "chapter_13_videos already cloned!\n"
     ]
    }
   ],
   "source": [
    "# install github clone - allows for easy cloning of subdirectories\n",
    "!pip install github-clone\n",
    "from pathlib import Path \n",
    "\n",
    "# clone datasets\n",
    "if not Path('chapter_13_datasets').is_dir():\n",
    "    !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/13_Multilayer_perceptrons/chapter_13_datasets\n",
    "else:\n",
    "    print('chapter_13_datasets already cloned!')\n",
    "\n",
    "# clone library subdirectory\n",
    "if not Path('chapter_13_library').is_dir():\n",
    "    !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/13_Multilayer_perceptrons/chapter_13_library\n",
    "else:\n",
    "    print('chapter_13_library already cloned!')\n",
    "\n",
    "# clone images\n",
    "if not Path('chapter_13_images').is_dir():\n",
    "    !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/13_Multilayer_perceptrons/chapter_13_images\n",
    "else:\n",
    "    print('chapter_13_images already cloned!')\n",
    "\n",
    "# clone videos\n",
    "if not Path('chapter_13_videos').is_dir():\n",
    "    !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/13_Multilayer_perceptrons/chapter_13_videos\n",
    "else:\n",
    "    print('chapter_13_videos already cloned!')\n",
    "\n",
    "        \n",
    "# append path for local library, data, and image import\n",
    "import sys\n",
    "sys.path.append('./chapter_13_library') \n",
    "\n",
    "# backend file\n",
    "import LS_sigmoid\n",
    "from multilayer_med_library import superlearn_setup\n",
    "\n",
    "# data path\n",
    "import pickle\n",
    "data_path_1 = 'chapter_13_datasets/2d_classification_data_v1_entropy.csv'\n",
    "data_path_2 = 'chapter_13_datasets/MNIST_subset.pickle'\n",
    "\n",
    "# image paths\n",
    "image_path_1 = \"chapter_13_images/bad_convex_comparison.png\"\n",
    "\n",
    "# video paths\n",
    "video_path_1 = 'chapter_13_videos/animation_1.mp4'\n",
    "\n",
    "# standard imports\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import Image, HTML\n",
    "from matplotlib import gridspec\n",
    "import autograd.numpy as np\n",
    "from base64 import b64encode\n",
    "\n",
    "def show_video(video_path, width = 1000):\n",
    "    video_file = open(video_path, \"r+b\").read()\n",
    "    video_url = f\"data:video/mp4;base64,{b64encode(video_file).decode()}\"\n",
    "    return HTML(f\"\"\"<video width={width} controls><source src=\"{video_url}\"></video>\"\"\")\n",
    "\n",
    "# this is needed to compensate for matplotlib notebook's tendancy to blow up images when plotted inline\n",
    "%matplotlib inline\n",
    "from matplotlib import rcParams\n",
    "rcParams['figure.autolayout'] = True\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2k8EuzrYeDmT"
   },
   "source": [
    "## Non-convexity and multi-layer perceptrons"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WSCBFfeceDmT"
   },
   "source": [
    "Models employing multi-layer perceptron units are often considerably non-convex, however they often exhibit a variety of non-convexity that we can fairly easily deal with using advanced optimization methods. Indeed we saw simple exemplars of this behavior back in Sections 6.1.4 and 6.2.1, where we described the general behavior of the Least Squares cost when performing logistic regression when employing either the *sigmoid* or $\\text{tanh}$ function. Interpreting the models used in both instances through the lens of multi-layer perceptrons, we can say that *both* are simple exemplars of a single hidden layer network model. For example, the Least Squares cost proposed in Section 6.1.4 consists of a model employing one unit of a single hidden layer network with sigmoid activation, i.e.,\n",
    "\n",
    "\\begin{equation}\n",
    "\\text{model}\\left(x,\\Theta\\right) = \\sigma\\left(w_0 + w_1x \\right).\n",
    "\\end{equation}\n",
    "\n",
    "Here we can see that the weights of the final linear combination are *fixed*, with the bias set to zero and the weight touching $\\sigma\\left(\\cdot\\right)$ set to one. In Example 3 of Section 6.1.4 we plotted the surface of the Least Squares cost employing this network model using a simple toy dataset, which we show again in the figure below for convenience."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "IxBVcAXkeDmT",
    "outputId": "c4dc0fcb-3451-46bc-e847-7c8a4572b844"
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 600x300 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# load data\n",
    "data = np.loadtxt(data_path_1, delimiter = ',')\n",
    "\n",
    "# create an instance of the visualizer and plot\n",
    "demo = LS_sigmoid.Visualizer(data)\n",
    "demo.plot_costs(viewmax = 25, view = [21,121])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bMz0uiUCeDmU"
   },
   "source": [
    "Examining the general shape of the cost function in the right panel, firstly we can clearly see that it is non-convex. Several portions of the cost surface - on either side of the *long narrow valley* containing the cost's global minimum - *are almost completely flat*, likely containing *saddle points* that can halt most basic optimization schemes. As described in Chapter 4 (and Section 4.5 in particular), without serious adjustment second order methods struggle to minimize functions like this. These aspects of the non-convexity are also very problematic for the *basic* gradient descent algorithm - as detailed in Section 3.5. However gradient descent can be easily enhanced to deal with *precisely* these issues - as discussed in Sections 3.6 - 3.9.  Indeed both aspects of the non-convexity we see here -  both the *long narrow valley* and the *flat areas* potentially containing saddle points - were precisely the motivation for *momentum* (see Section 3.7) and *gradient normalization* (see Section 3.8) respectively.  Combining these two enhancements (see Section 3.9), in addition to mini-batch optimization (see Section 3.10), can further enhance gradient based methods so that they can more easily minimize cost functions such as this one.  Indeed back in Example 3 of Section 6.1.4 where this particular cost was first described, we show that the *normalized gradient descent* alone can properly minimize it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "esNdEyuTeDmV"
   },
   "source": [
    "In general cost functions employing neural network models have non-convex shapes that share the kinds of basic characteristics - long narrow valleys, flat areas, and many saddle points - seen in the example above. These sorts of non-convex functions can be effectively minimized in general using advanced optimization methods, the most popular of these being the sort of enhanced gradient descent algorithms described in the latter part of Chapter 3. Even when these cost functions have many *local minima* these tend to lie at a depth close to that of their global minima, and thus tend to provide similar performance if found via local optimization.  An artistic depiction of this sort of prototypical cost, the kind often experienced with neural network models, is shown in the left panel of the figure below.  This is starkly different than a kind of hypothetical non-convex cost - not often encountered with neural networks - whose global minima lie considerably lower than its local minima, like the one shown in the right panel of the figure below.  There are no enhancements one can make to any local optimization method to enable it to effectively deal with such a cost function, with the only practical salve being to make many optimization runs starting from random initial points to see if a global minima can be reached during some run.   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "h0iV-8V-eDmV",
    "outputId": "44d27371-a99d-4f15-f6a7-fa65d6d7cfc1"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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BAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQeBBx6H1aSkQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAICvg0JudVjECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIEHAYfeh5VkJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyAoMuURLJUwm29YAAAAASUVORK5CYII=",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(image_path_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JeiaQ19keDmV"
   },
   "source": [
    "<figure>\n",
    "<figcaption> <strong>Figure 2:</strong> <em> (left panel) An artistic depiction of the sort of prototypical cost function seen when employing neural network models. (right panel) An artistic depiction of the sort of bad (difficult to properly minimize) non-convex cost rarely found when using neural networks.  See text for further details.  </em>\n",
    "</figcaption>\n",
    "</figure>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Wt9c20ODeDmV"
   },
   "source": [
    "#### <span style=\"color:#a50e3e;\">Example 1. </span>  Comparing standard gradient descent to "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "k2z-Mu9-eDmW"
   },
   "source": [
    "In this Example we use $P = 50,000$ random datapoints from the MNIST dataset first detailed in Example 1 of Section 7.6, performing $C = 10$ class classification using a four hidden layer network with $10$ units per layer and a $\\text{tanh}$ activation (these were chosen arbitrarily for the purposes of this example).  Here we compare the efficacy of two advanced optimization techniques - gradient normalization and mini-batch optimization - detailed in Sections 3.8 and 3.10 respectively - over the standard gradient descent algorithm in minimizing the associated Multiclass Softmax cost over this data.  \n",
    "\n",
    "In the first figure below we show a comparison of the number of misclassifications during the first $10$ steps of a run of gradient descent and its normalized analog.  In the second figure we show the same results, only now compare the standard algorithm to a mini-batch version using a batch size of $200$.  Both advanced gradient algorithms drastically outperform the standard approach here.  Which advanced approach - or combination of them - works best in practice can vary from dataset to dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "FXWP4TMleDmW"
   },
   "outputs": [],
   "source": [
    "# load data\n",
    "with open(data_path_2, \"rb\") as input_file:\n",
    "    data = pickle.load(input_file)\n",
    "    \n",
    "x_sample = data[0]\n",
    "y_sample = data[1] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "8cwf5GEeeDmW",
    "outputId": "93705704-031a-4e13-a318-e213defa28f0"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import the v1 library\n",
    "mylib0 = superlearn_setup.Setup(x_sample,y_sample)\n",
    "\n",
    "# choose features\n",
    "layer_sizes = [784,10,10,10,10]\n",
    "\n",
    "# choose features\n",
    "mylib0.choose_features(name = 'multilayer_perceptron',layer_sizes = layer_sizes,activation = 'tanh')\n",
    "\n",
    "# choose normalizer\n",
    "mylib0.choose_normalizer(name = 'standard')\n",
    "\n",
    "# choose cost\n",
    "mylib0.choose_cost(name = 'multiclass_softmax')\n",
    "\n",
    "# fit an optimization\n",
    "alpha = 10**(-1)\n",
    "mylib0.fit(max_its = 10,alpha_choice = alpha)\n",
    "# mylib0.fit(max_its = 10,alpha_choice = alpha,beta = 0.9)\n",
    "mylib0.fit(max_its = 10,alpha_choice = alpha,normalize = True)\n",
    "# mylib0.fit(max_its = 10,alpha_choice = alpha,optimizer = 'RMSprop')\n",
    "\n",
    "# show histories\n",
    "labels = ['standard','normalized']\n",
    "mylib0.show_histories(labels = labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "EchoHxNYeDmW",
    "outputId": "4c07aa55-302d-4836-b689-1345e5357d90"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import the v1 library\n",
    "mylib0 = superlearn_setup.Setup(x_sample,y_sample)\n",
    "\n",
    "# choose features\n",
    "layer_sizes = [784,10,10,10,10]\n",
    "\n",
    "# choose features\n",
    "mylib0.choose_features(name = 'multilayer_perceptron',layer_sizes = layer_sizes,activation = 'relu')\n",
    "\n",
    "# choose normalizer\n",
    "mylib0.choose_normalizer(name = 'standard')\n",
    "\n",
    "# choose cost\n",
    "mylib0.choose_cost(name = 'multiclass_softmax')\n",
    "\n",
    "# fit an optimization\n",
    "alpha = 10**(-1)\n",
    "mylib0.fit(max_its = 10,alpha_choice = alpha)\n",
    "mylib0.fit(max_its = 10,alpha_choice = alpha,batch_size = 200)\n",
    "# mylib0.fit(max_its = 10,alpha_choice = alpha,normalize = True)\n",
    "# mylib0.fit(max_its = 10,alpha_choice = alpha,optimizer = 'RMSprop')\n",
    "\n",
    "# show histories\n",
    "labels = ['standard','minibatch']\n",
    "mylib0.show_histories(labels = labels)"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "include_colab_link": true,
   "provenance": []
  },
  "kernelspec": {
   "display_name": "venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.15"
  },
  "toc": {
   "colors": {
    "hover_highlight": "#DAA520",
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    "running_highlight": "#FF0000",
    "selected_highlight": "#FFD700",
    "sidebar_border": "#EEEEEE",
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   },
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   "nav_menu": {
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    "width": "252px"
   },
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   "threshold": 4,
   "toc_cell": false,
   "toc_section_display": "block",
   "toc_window_display": false,
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 },
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 "nbformat_minor": 1
}
